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Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

作者： Passant Elagroudy Rufat Rzayev Tonja-Katrin Machulla Huy Viet Le Tilman Dingler Lars Lischke Sarah Clinch Geoffrey Ward Albrecht Schmidt German Research Centre for Artificial Intelligence (DFKI) Kaiserslautern Germany and RPTU Kaiserslautern Kaiserslautern Germany Interactive Media Lab Dresden TUD Dresden University of Technology Dresden Germany Institute for Media Research TU Chemnitz Chemnitz Germany University of Stuttgart Stuttgart Germany Industrial Design Engineering Delft University of Technology Delft Netherlands User Centric Data Science Vrije Universiteit Amsterdam Amsterdam Netherlands Department of Computer Science The University of Manchester Manchester United Kingdom Department of Psychology University of Essex Essex United Kingdom LMU Munich Munich Germany

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Climate Change Resilience of Freshwater Supply on Small Islands: Research Gaps and Strategies for a Case Study in Grand Bahama

SSRN

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SSRN 2024年

作者： Imig, Anne Welsh, Kristen Klausner, Sophia Hotta, Carolina Iwane McKenzie, Zeko Perosa, Francesca Stephens, Mark Turner, Amber Thomas, John Chaves, Henrique Leite Bowen-O'Connor, Clare Moxey, Andrew Dokou, Zoi Rein, Arno Hydrogeology School of Engineering and Design Technical University of Munich Germany Small Island Sustainability Programme University of The Bahamas Nassau Bahamas Geosciences Department Oberlin College OberlinOH United States Hydrology and River Basin Management School of Engineering and Design Technical University of Munich Germany Department of Earth and Biological Sciences Loma Linda University Loma LindaCA United States School of Chemistry Environmental and Life Sciences University of The Bahamas Nassau Bahamas University of the West Indies Barbados Strata Environmental Nassau Bahamas Watershed Management Lab EFL – School of Technology University of Brasilia DF Brasilia Brazil University of Trinidad and Tobago Trinidad and Tobago School of Chemistry Environmental and Life Sciences University of The Bahamas Freeport Bahamas Department of Civil Engineering College of Engineering and Computer Science California State University SacramentoCA United States

Study Region: Grand Bahama Island, the Commonwealth of The Bahamas. Study Focus: In Grand Bahama, due to its low elevation, sea level rise and flooding during hurricane events has led to the salinization of groundwater, which is the only source of potable water for the island. In this study, we assessed available literature of groundwater resources in Grand Bahamas to identify key challenges and knowledge gaps for the protection of the potable water supply. A literature review guided our assessment of various sustainable groundwater management approaches for the island. Understanding the hydrogeology and identifying strategies to maintain the freshwater lenses in Grand Bahama are key to ensure the island remains *** Hydrological Insights for the Region: Existing hydrogeological data highlight the urgent need to improve the island’s water supply system and to identify safe groundwater yields to sustain its drinking water supply. Based on analysis of these data, we propose the implementation of nature-based solutions, such as managed aquifer recharge and reforestation measures, to restore the groundwater ecosystem service of freshwater supply. Furthermore, to ensure effective water supply management, legislation and regulations should be adapted to actively involve both institutions and the public in the decision-making process. The results of this review are applicable to other small island nations around the world that are facing the effects of climate change and seawater intrusion. © 2024, The Authors. All rights reserved.

关键词： Groundwater resources

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What's bothering developers in code review?

What's bothering developers in code review?

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IEEE/ACM International Conference on Software engineering: Software engineering in Practice Track (ICSE-SEIP)

作者： Emma Sö derberg Luke Church Jü rgen Bö rstler Diederick C. Niehorster Christofer Rydenfä lt Dept. of Computer Science Lund University Sweden Lund University University of Cambridge Sweden United Kingdom Dept. of Software Engineering Blekinge Institute of Technology Sweden Dept. of Psychology Humanities Lab Lund University Sweden Dept. of Design Sciences Lund University Sweden

The practice of code review is widely adopted in industry and has been studied to an increasing degree in the research community. However, the developer experience of code review has received limited attention. Here, ...

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Smartphone camera oximetry in an induced hypoxemia study

arXiv

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arXiv 2021年

作者： Hoffman, Jason S. Viswanath, Varun Ding, Xinyi Thompson, Matthew J. Larson, Eric C. Patel, Shwetak N. Wang, Edward Paul G. Allen School of Computer Science and Engineering University of Washington United States Department of Electrical and Computer Engineering University of California San Diego United States The Design Lab University of California San Diego United States Department of Computer Science Southern Methodist University United States Department of Family Medicine University of Washington United States Department of Electrical and Computer Engineering University of Washington United States

Hypoxemia, a medical condition that occurs when the blood is not carrying enough oxygen to adequately supply the tissues, is a leading indicator for dangerous complications of respiratory diseases like asthma, COPD, and COVID-19. While purpose-built pulse oximeters can provide accurate blood-oxygen saturation (SpO2) readings that allow for diagnosis of hypoxemia, enabling this capability in unmodified smartphone cameras via a software update could give more people access to important information about their health, as well as improve physicians’ ability to remotely diagnose and treat respiratory conditions. In this work, we take a step towards this goal by performing the first clinical development validation on a smartphone-based SpO2 sensing system using a varied fraction of inspired oxygen (FiO2) protocol, creating a clinically relevant validation dataset for solely smartphone-based methods on a wide range of SpO2 values (70%-100%) for the first time. This contrasts with previous studies, which evaluated performance on a far smaller range (85%-100%). We build a deep learning model using this data to demonstrate accurate reporting of SpO2 level with an overall MAE=5.00% SpO2 and identifying positive cases of low SpO22 monitoring, and we provide the data from the FiO2 study in open-source format, so that others may build on this work. © 2021, CC BY-NC-ND.

关键词： Smartphones

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Deep learning models for enhanced in-field maize leaf disease diagnosis

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Machine Learning with Applications 2025年 20卷

作者： Nakatumba-Nabende, Joyce Murindanyi, Sudi Department of Computer Science College of Computing and Information Sciences Makerere University Uganda Marconi Machine Learning Lab College of Engineering Design Art and Technology Makerere University Uganda Makerere Center for Artificial Intelligence and Data Science Makerere University Uganda

Maize leaf diseases significantly threaten crop yields, and there is need for accurate, and accessible diagnostic tools. This research addresses this need by developing and evaluating deep learning (DL) and machine learning (ML) models for in-field classification and detection of four critical maize diseases: Maize Leaf Blight, Maize Lethal Necrosis, Maize Streak Virus, and Fall Armyworm damage. Utilizing field imagery captured via digital cameras and smartphones across Uganda, Tanzania, Ghana, and Namibia, we developed and compared custom Convolutional Neural Networks (CNNs), transfer learning (MobileNetV2, InceptionResNetV2), Vision Transformers (ViT), and classical ML models. For detection, a transformer-enhanced YOLOv10 architecture was implemented. Explainable AI (XAI) techniques (Grad-CAM, LIME) were incorporated to ensure model transparency. MobileNetV2 achieved the highest classification accuracy (97%), while the enhanced YOLOv10 reached a mean Average Precision (mAP) of 0.995 for object detection. The best models were integrated into a mobile application deployed on edge devices for real-time diagnosis by smallholder farmers in Uganda, with performance validated through field tests. This study demonstrates a powerful, interpretable, and field-deployable solution combining advanced DL, transformers, and XAI for effective maize health management. © 2025

关键词： Convolutional neural networks

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The Stretchy Strap: supporting encumbered interaction with guitars

引用

Interface 2023年第1期52卷

作者： Juan Martinez Avila Adrian Hazzard Chris Greenhalgh Steve Benford Andrew McPherson a Mixed Reality Laboratory School of Computer Science The University of Nottingham Nottingham UK b Augmented Instruments Lab School of Electronic Engineering and Computer Science Queen Mary University of London. Dyson School of Design Engineering Imperial College London London UK

Guitarists struggle to play their instruments while simultaneously using additional computing devices (i.e., encumbered interaction). We explored designs with guitarists through co-design and somaesthetic design workshops, learning that they (unsurprisingly) preferred to focus on playing their guitars and keeping their instruments’ material integrity intact. Subsequently, we devised an interactive guitar strap controller, which guitarists found promising for tackling encumbered interaction during instrumental transcription, learning and practice. Our design process highlights three strategies: considering postural interaction, applying somaesthetic design to interactive music technology development, and augmenting guitar accessories.

关键词： Augmented guitars Encumbered interaction Somaesthetic design User-centred design E-textiles Embodied interaction Postural interaction Learning and practicing music

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DenseNet for Breast Tumor Classification in Mammographic Images 1st

DenseNet for Breast Tumor Classification in Mammographic Ima...

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1st International Conference on Bioengineering and Biomedical Signal and Image Processing, BIOMESIP 2021

作者： Jiménez Gaona, Yuliana Rodriguez-Alvarez, María José Espino-Morato, Hector Castillo Malla, Darwin Lakshminarayanan, Vasudevan Departamento de Química y Ciencias Exactas Universidad Técnica Particular de Loja San Cayetano Alto s/n CP1101608 Loja Ecuador Valencia46022 Spain Theoretical and Experimental Epistemology Lab School of Optometry and Vision Science Waterloo Canada Department of Systems Design Engineering Physics and Electrical and Computer Engineering University of Waterloo WaterlooONN2L3G1 Canada Valencia46022 Spain

ISBN: (纸本)9783030881627

Breast cancer screening is an efficient method to detect breast lesions early. The common screening techniques are tomosynthesis and mammography images. However, the traditional manual diagnosis requires an intense workload for pathologists, and hence is prone to diagnostic errors. Thus, the aim of this study was to build a deep convolutional neural network method for automatic detection, segmentation, and classification of breast lesions in mammography images. Based on deep learning the Mask-CNN (RoIAlign) method was developed to automate RoI segmentation. Then feature extraction, selection and classification were carried out by the DenseNet architecture. Finally, the precision and accuracy of the model was evaluated by the AUC, accuracy and precision metrics. To summarize, the findings of this study show that the methodology may improve the diagnosis and efficiency in automatic tumor localization through medical image classification. © 2021, Springer Nature Switzerland AG.

关键词： Mammography

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Implementation of Grover's algorithm on the IBMQ: Constraints and error assessment

Implementation of Grover's algorithm on the IBMQ: Constraint...

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Photonics for Quantum 2021

作者： Eldridi, Asma Gueddana, Amor Lakshminarayanan, Vasudevan University of Carthage Department of Electrical Engineering National Engineering School of Carthage ENICarthage Tunis2035 Tunisia University of Carthage Higher School of Communication of Tunis Sup'Com Green and Smart Communication Systems Lab Gres'Com Ariana2083 Tunisia University of Waterloo School of Optometry and Vision Science Theoretical and Experimental Epistemology Lab TEEL 200 University Avenue West WaterlooONN2l 3G1 Canada University of Waterloo Department of Physics Department of Electrical and Computer Engineering Department of Systems Design Engineering 200 University Avenue West WaterlooONN2l 3G1 Canada

ISBN: (纸本)9781510645264

We use the IBMQ machine to implement a quantum database circuit. The database is made of a single multi-column table with multiple superposed records using Toffoli, CNOT and single quantum qubit gates. We present an optimized quantum circuit which allows us to select an item from the table, according to a specific oracle. Our circuit is based only on a single auxiliary qubit to perform the Selective Inversion (SI) and the Inversion Around the Average (IAA), which constitute the Grover operator. We analyze the difference between the generated transpired circuits while executing the original circuit on different IBMQ machines, namely the Melbourne and Athens quantum machines. We discuss the physical constraints causing the difference between the simulation on the composer and the executions of the circuits on the real IBMQ devices. © 2021 Copyright SPIE.

关键词： Timing circuits

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Exploring the Effects of Social VR Coupling Modes on Engagement and Task Performance for Older Adults 25

Exploring the Effects of Social VR Coupling Modes on Engagem...

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Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems

作者： Thuan T Vo Satabdi Das Shamim Noroozi Lakshay Dang Jaisie Sin Jennifer N Boger Jennifer Jakobi Khalad Hasan University of British Columbia Kelowna British Columbia Canada Computer Science The University of British Columbia Kelowna British Columbia Canada School of Engineering University of British Columbia-Okanagan Kelowna British Columbia Canada Okanagan Visualization and Interaction Lab The University of British Columbia Okanagan Kelowna British Columbia Canada Carleton University Ottawa Ontario Canada Systems Design Engineering University of Waterloo Waterloo Ontario Canada and The University of British Columbia British Columbia Canada Aging in Place Research Cluster The University of British Columbia Okanagan British Columbia Canada The University of British Columbia Okanagan Kelowna British Columbia Canada

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Converged reconfigurable intelligent surface and mobile edge computing for space information networks

arXiv

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arXiv 2021年

作者： Cao, Xuelin Yang, Bo Huang, Chongwen Yuen, Chau Zhang, Yan Niyato, Dusit Han, Zhu Engineering Product Development Pillar Singapore University of Technology and Design Singapore Singapore College of Information Science and Electronic Engineering Zhejiang Provincial Key Lab of information processing communication and networking International Joint Innovation Center Zhejiang University China Department of Informatics University of Oslo Norway School of Computer Science and Engineering Nanyang Technological University Singapore Singapore Department of Electrical and Computer Engineering University of Houston United States

Space information networks (SIN) are facing an ever-increasing thirst for high-speed and high-capacity seamless data transmission due to the integration of ground, air, and space communications. However, this imposes a new paradigm on the architecture design of the integrated SIN. Recently, reconfigurable intelligent surfaces (RISs) and mobile edge computing (MEC) are the most promising techniques, conceived to improve communication and computation capability by reconfiguring the wireless propagation environment and offloading. Hence, converging RISs and MEC in SIN is becoming an effort to reap the double benefits of computation and communication. In this article, we propose an RIS-assisted collaborative MEC architecture for SIN and discuss its implementation. Then we present its potential benefits, major challenges, and feasible applications. Subsequently, we study different cases to evaluate the system data rate and latency. Finally, we conclude with a list of open issues in this research area. Copyright © 2021, The Authors. All rights reserved.

关键词： Mobile edge computing

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